This specification describes an advance in the compression and reconstruction of data that can typically be represented as a matrix or a sequence of matrices. Each matrix may then be represented graphically. Such data is typically analysed and represented in one or more ways to assist in its interpretation by a human or a computer programmed to provide assistance in such matters. Such data could relate to a multitude of matters.
It is a truism that the larger the amount of data collected by one or more sensors the more accurate and useful the analysis of that data into information will be. Therefore, it is one thing to collect data that once analysed could be of use, the challenge is often how the data collected is going to be communicated to where it can be analysed and then used in the most appropriate manner.
Low data communication bandwidths exist for one or more reasons for many communications systems and the data to be transmitted can thus take inordinate periods of time to transmit because of the low data rate achievable on the channel. Even when communication channels of adequate bandwidth are available, the priority of the data may be such that it is not of adequate benefit to devote that available bandwidth to the task of communicating the data to where it may be of greatest value.
In this specification a potential solution to this problem is described that uses compression and reconstruction algorithms to enable the transmission of data that can be represented as a numerical matrix or a sequence of images, this is true for any data that can be represented as a numerical matrix or a sequence of matrices. The algorithms disclosed may reduce data size for some applications to such an extent that sensors or electronic systems that were considered to provide so much data as to be impractical for transmission on available channels in a useful time frame can now transmit their data in real time or within an acceptable time.